Characterization of white matter asymmetries in the healthy human brain using Diffusion MRI fixel-based analysis
AuthorHonnedevasthana Arun, Arush
AffiliationFlorey Department of Neuroscience and Mental Health
Document TypeMasters Research thesis
Access StatusOpen Access
© 2020 Arush Honnedevasthana Arun
Magnetic resonance imaging (MRI) has revolutionized the way to investigate brain structural connectivity non-invasively. Diffusion MRI can be used to obtain local estimates of the white matter fibre orientations in the brain, which in turn can be used to study changes in the local fibre specific properties and/or in conjunction with fiber-tracking algorithm to reconstruct a representation of the white matter pathways in the brain. In recent years, the Diffusion Tensor model has played an important role in modelling the diffusion of water within white matter bundles. Diffusion tensor derived metrics such as fractional anisotropy (FA) have been used extensively for investigating white matter using approaches such as voxel-based analysis. One of the limitations of the diffusion tensor model is that it is not capable of appropriately modelling regions that have complex fibre architecture (such as crossing fibres). This makes tensor-derived measures unreliable measures to assess the white matter. Recent contributions toward the study of brain asymmetry have suggested asymmetry of brain anatomy and function are observed in the temporal, frontal, and parietal lobes. Several studies have used diffusion tensor model to study asymmetry in various regions of the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain. This research aims to provide to provide a more robust characterization of structural white matter asymmetries than those previously derived using the tensor model, by using quantitative measures derived from the spherical deconvolution model, and a whole-brain data-driven statistical inference framework such as Fixel-Based Analysis, that is both sensitive and specific to crossing fibres; we furthermore apply this approach to a state-of-the-art publicly available diffusion MRI dataset.
Keywordsdiffusion MRI; MRI; Asymmetry; Healthy human brain
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